That Neuroscience Guy - The That Neuroscience Guy Lecture Series - Part 1

Episode Date: April 28, 2025

Recently, Dr Krigolson gave an invited lecture at Indiana University titled "Why We Do the Dumb Things We Do". Now we are delivering that lecture to you in a three part series starting with basics of decision making. 

Hi, my name is Lone Wolf Krogolson. Hi, I'm Brayden Allen. I'm a neuroscientist at the University of Victoria. I'm a neuroscience undergraduate student at Indiana University. And we're the Neuroscience Guys. Welcome to the podcast. Last week, I had the honor and pleasure of being invited by the Neuroscience Club at Indiana University to come and give a talk for the club.

It was great for two reasons. One I did my master's degree at Indiana University and I have fond memories there and it's where I fell in love with neuroscience. Second of all, one of the listeners to the podcast and now a friend of mine, Braden, who's a neuroscience student at Indiana University, was the one that reached out to me, invited me. And it was such a nice invite and the way it was worded, it just made me want to come and fit it into my schedule.

So on today's podcast, it's going to be a bit different. I'm going to give you the lecture that I gave to the students at Indiana University. It's called Why We Do The Dumb Things We Do. We're going to break it into two parts because it's quite long relative to our normal episodes. And it's sort of an overview of human decision-making. It's an all-in-one. So it's stuff that we overview of human decision making. It's an all in one.

So it's stuff that we've talked about on the podcast before. Some of it's new. Some of it is as you've heard before, but it's a, it's the talk I gave at Indiana university. I actually wanted to record it and give you the live version. Uh, but the problem was I couldn't get my audio equipment to work and I just gave up it because I had to give the talk. So you're not going to get the normal editing with this. I'm going to make some mistakes and have to go back and repeat things. So this is like you were sitting in the room that night because when I obviously Matt does a great job editing the sound,

but and he cleans up a lot of my mistakes. but tonight you're just gonna get the raw deal. This is what the lecture would have sounded like and I hope you found it interesting. So why we do the dumb things we do. Oh, before I get rolling, I'll say that I'm gonna post a slide deck onto the blog, thatneuroscienceguy.com. If you look at the blog, there'll be a blog entry.

So there'll be a PDF of the slides. So you can follow along with visuals if you'd like to as well. Okay, without further ado, why we do the dumb things we do. So our brain, as we know, is made up of 86 billion or so neurons, and all of the decisions that we make are just a product of neurons firing. It really boils down to that. There's a lot of other stuff in there, those glial cells holding things together and other structures, cerebrospinal fluid and things like this, but at the end of the day it's just a bunch of neurons firing. And those neurons when they fire in different brain regions, they basically,

you know, if they fire in the prefrontal cortex, that's our analytical decision making system that we've talked about before. If they fire in the amygdala, that's our emotional response. And at the end of the day, it's these brain regions that lead us to doing the dumb things that we do. Now, I'm going to start with the story, which is how I ended up at Indiana University. I don't know if this was a dumb decision, but it was definitely an interesting decision. I was at the main train station at Venice, Italy. This is a long time ago. I was a high school teacher at a school in England. It was spring break and I had never been to Venice.

So I actually flew to Munich, took a train through to Venice and I spent a couple of days wandering that amazing city. And I at the time was a high school teacher. Like I said, I was a basketball coach and that was my life. And I hadn't really thought about neuroscience. Now, I was sitting there waiting for the train and relaxing. And I started thinking about grad school because a professor of mine had said, well, Hey, you know, you should go to grad school one day. Now, as I said,

this is a long time ago, the internet was like a video game. You, I went into the station and there was a kiosk, had a keyboard and a track ball, and you put some money in and you were on the internet. And I started Googling best kinesiology graduate programs in North America because I was into sports and I thought that was my future and up pops Indiana University.

And this was interesting for two reasons. One, it said it was the best Kinesiology grad program in North America. I don't know if that's a true statement, but that's what it said. And second, I was a massive Indiana basketball fan. The first college game I'd ever seen was the 87 championship game when Indiana beat Syracuse.

So I emailed the contacts and sort of said, look, I'd love to come to grad school at Indiana. What do I do? And I ended up having to write the graduate record exam. But lo and behold, I ended up at Indiana University. And my declared major, sports marketing. I wanted to be a basketball coach. But we had an elective slot. And there were a variety of courses you could take,

and one of them was about neuroscience, and there was a blurb about learning in the brain, and I thought, you know, if I'm gonna be a basketball coach, what a great thing to learn, you know? This would be really useful. So in my very first semester of grad school, I went to this class, and an incredible man, Dr. David Kaseya, came in and he started drawing pictures of neurons and talking about

synaptic plasticity and learning. And I just fell in love. My entire life changed. Within two weeks, I'd switched into the motor control program, which is basically the neuroscience of human movement. I'd stopped, you know, I finished coaching that year, but I knew that coaching wasn't the future. And, you know, that put me on the path to a PhD in neuroscience and the rest is history. But I made that decision just on the spur of the moment to change my life. And like I said, not a dumb decision, but what I'm

going to walk you through is, you know, what was going on in my head and you've heard similar things in the past, but that's not going to be the end of it. It's going to walk you through is, you know, what was going on in my head and you've heard similar things in the past, but that's sort of the framing the talk, you know, that we make these incredible decisions and why do we make them? Because it was literally, you know, in a train station in Venice, Italy, where I decided to go to grad school and now I'm a full professor of neuroscience and had no clue it was gonna happen. Now to truly understand decision-making, I think

there's two people you really get to need to know. There's John Stuart Mill in about 1861, he came up with the idea of utilitarianism. No other people had talked about it, but he's one of the people that gets credit for truly framing it, and utilitarianism of the people that gets credit for truly framing it. And utilitarianism is the idea that people seek actions that increase utility and avoid actions that decrease utility. Now what is utility? That's a fancy word used in economics to talk about reward.

So if you frame this from a neuroscience perspective or a psychological perspective, you'd say people seek actions that increase reward, all right, make our lives better, and you avoid actions that decrease reward. All right, so we choose things that make us happy, things that are rewarding, and we avoid things that don't make us happy. And this seems to be a driving force within our brain. You can talk back to the original sort of fight or flight responses, but we also have this sort of desire to increase our utility, because it's a survival thing.

The more rewards you have, the better chance you have of surviving. And if you avoid things that aren't rewarding, you also have a better chance of surviving. The other person that we've talked about before that goes back even further that you have to think about when you're talking about decision-making is Huygens, Christian Huygens, who in 1657 came up with the idea of expected value. Now again, other people had talked about this.

He just gets a bunch of the credit. He basically defined an expected value as a value for something times the probability. All you do is you wander around and you compute expected values and you use these expected values to determine choices. So if you decided to have pizza tonight as opposed to sushi, pizza would have had a higher expected value. And that value doesn't have to be a financial thing. And we're gonna get into that. And we'll talk about how probability works and then we'll bring it all back to the brain.

So this is a classic expected value problem. If you're following along with the slides, I'll read it out in case you don't have them. Problem one, would you play a gamble that has a 40% chance to win $1,000 or a 70% chance to win $600? Now from an expected value perspective, all you do is you compute the expected value here.

You take 40% times 100, and you get an expected value of $400 or 400 and you take 70% of 600 which I believe is $420 and that is a higher expected value. So you should choose the gamble 70% chance to win $600 because your expected value is higher. This of course is why you should never play the lottery, right? Because while the value of winning the lottery is massive, I think where I live it's about $55 million right now, the probability is so low that it's less than the expected value of not playing.

Because say your ticket cost you $3, well three dollars times a hundred percent is three dollars, which is a larger expected value than you get from playing the lottery, which is you know it's fractions of pennies. So you're actually losing money every time you play the lottery and we all know that but from an expected value perspective you should never play the lottery. This is also why Las Vegas works right because the expected value of any casino game is basically less than 0.5. So you're going to lose money more than half the time. So do brains actually encode expected values?

And yeah, there's evidence of this. Some work that was done at New York University by the Glimcher Lab, they basically had monkeys making expected value choices. They were staring at a screen and they had to secot or move their eyes to a target on the left or the right. And what they learned is that one of these choices, like these choices led to rewards, it's just, I think it was apple juice in this case, but one had a higher probability

of giving juice than the other. So there's an expected value element. And what they learned is that the monkeys actually learned to choose the higher expected value option. And they played around with the probabilities and the amounts of the rewards, but the monkeys were able to figure it out. And when they measured brain activity,

they actually found that neurons in a part of the brain, but the monkeys were able to figure it out. And when they measured brain activity, they actually found that neurons in a part of the brain, in the monkey brain called the lateral interparietal cortex or area LIP, they basically scaled in the firing rate to the expected utility or the expected value. So they actually saw these neurons firing away and the amount of firing was proportional to the expected value.

So this was seen as pretty conclusive proof that the monkey brain was encoding expected value. And there's been lots of other studies that have shown similar results. So brains encode expected value. Well, it's monkeys. What about humans? Well, in some work that was done in Germany, I always love this study. I think it's classic. It's called Cultural Objects Modulate Reward Circuitory. And what they did in this study is they had people basically rate cars for attractiveness.

And there were three categories of cars. There were sports cars, there were limousines, and there were small cars. And if you're in the slides, there's actually a photo example of the type of stimuli they used. And the stimuli look pretty boring because they have to control for color and luminance and all these things.

But at the end of the day, one category is clearly sports cars, one's clearly limousines and one's clearly small cars. And they did this in an FMRI scanner. They basically had people see these cars, and then they had to rate the cars in terms of attractiveness. So how attractive did you find this given car? And when they looked at their results, what they found

was that sports cars had the highest attractiveness, followed by limousines, with small cars being rated the least attractive. But when they looked at their fMRI data they found that neurons in the ventral striatum, like the ventral striatum itself, were firing and that firing in the ventral striatum was proportional to the attractiveness ratings. So there was more firing for sports cars and there was a lot less firing for small cars with limousines kind of sitting in the middle. But what sports cars, and there was a lot less firing for small cars

with limousines kind of sitting in the middle. But what's interesting, and again, if you go to the slides, thatneuroscienceguy.com, go to the blog, you'll find them, you'll see that the pattern is very similar. The actual magnitudes are different because you're talking ratings versus neural activity, but it's very interesting to see again, the brain encoding value in this case

in the form of attractiveness. Now, just a quick thought on value. You have to remember that value, first of all, is not a money thing. It's a subjective thing. Like your favorite sweater might not be worth a lot of money, but it has high value for some reason to you.

Your favorite food might not be the most expensive food on the planet, but it's the food you like the most. The other point on value is that values aren't constant in our lives. Values change over time. This can be a short time scale. Imagine you're sitting there debating where you'd like to go on your next holiday. Would you like to go somewhere sunny? Or would you like to go somewhere, you know,

somewhere sunny where you can sit on the beach or somewhere cold where you can go skiing? And as you think about being cold, the value for skiing might go down and the value for being on a beach might go up. But then you might remember that you really have a lot of fun snowboarding. So the value for going on a beach might go up, but then you might remember that you really have a lot of fun snowboarding, so the value for going to the cold place goes up,

and the value for going to the beach goes down, because you can't do that. And then the way decision-making works is basically you have an individual threshold. We each have our threshold for a decision-making. Some people have a very low threshold, which means you make decisions very quickly, because the value reaches your threshold.

And for some of us, that threshold is set really high and this leads to indecisiveness. And of course, the threshold itself might change from decision to decision or across time as well. So it's important to remember that values aren't constant. They change throughout life. Just think of food. The food you liked as a kid, it's probably not the same food you like as an adult and probably not again as an older adult. And this is true of the music we listen to or any number of things.

Now, this leads us to a simple model of decision-making that goes back to Huygens. Always choose the highest expected value. There you go, that's all you need to know about decision-making. Compute your expected values and always choose the highest expected value. I just wanna say thank you again

to the Neuroscience Club at Indiana University and a special thank you to my new friend, Braden, for inviting me. It was such a great, great time coming back to Indiana and I really had fun giving the talk. Just a reminder, there's the website, right? Thatneuroscienceguy.com. These slides are going to be there. I'm going to post them as soon as I'm hit stop record. So they'll be up for you to look at.

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